Journal of Personality and Social Psychology1997, Vol. 73, No. 6. 1158-1176

Copyright 1997 by the American Psychological Association, Inc.0022-3514/97/53.0O

The Effect of Need and Ability to Achieve Cognitive Structuringon Cognitive Structuring

\bram Bar-Tal, Liat Kishon-Rabin, and Nili TabakTel Aviv University

The authors explored the hypothesis that the relationship between need for structure and cognitivestructuring behavior is moderated by the ability to achieve cognitive structure (AACS). Need forstructure is defined as the preference to use cognitive structuring as a means to achieve certainty.AACS refers to the extent to which individuals are able to use information-processing processes(cognitive structuring or piecemeal) consistent with ihe level of their need for structure. The authorssuggested that only under high AACS would there be a positive correlation between need for structureand cognitive structuring behavior. In contrast, under low AACS the correlation would be negative.To examine this hypothesis, the authors used different operationalizations of the need for structure,AACS, and cognitive structuring behavior. The results of the 5 studies in which this was doneconfirmed the hypothesis.

Social cognition research has pointed to the importance ofcognitive structuring. Researchers have claimed that it plays asignificant role in diverse phenomena such as dissonance andbalance (Kruglanski & Klar, 1987), person perception andmemory processes (Alba & Hasher, 1983; Allport, 1954; Ander-son, 1983; Cantor & Mischel, 1979; Hastie, Ostrom, Ebbesen,Wyer, Hamilton, & Carlston, 1980), stereotyping (Kruglanski &Freund, 1983; Stephan, 1989; Taylor, 1981), cognitive biases(Kruglanski & Ajzen, 1983), uncertainty (Bar-Tal, 1993,1994b; Bunder, 1962; Mayseles & Kruglanski, 1987), stress andcoping (Epstein & Meier, 1989; Wheaton, 1983), and attitude-behavior relationships (Jamieson & Zanna, 1989; Schlegel &DiTecco, 1982).

Cognitive structuring was defined by Neuberg and Newsom(1993) as the "creation and use of abstract mental representa-tions (e.g., schemata prototypes, scripts, attitudes, and stereo-types)—representations that are simplified generalizations ofprevious experience" (p. 113). Cognitive structuring allowsindividuals to attain certainty most efficiently. Bunder (1962)suggested that uncertainty is caused by individuals' inability toadequately structure or categorize information. The category-based process is more effective because it is relatively automatic,effort-free, and faster than the vigilance behavior (Brewer, 1988;Shiffrin & Schneider, 1977; Taylor & Crocker, 1981). In addi-tion, this process facilitates certainty by helping to omit incon-sistent or irrelevant information. Koriat, Lichtenstein, and Fisch-

"ibram Bar-Tal and Nili Tabak, Department of Nursing, School ofHealth Professions, Tel Aviv University, Tel Aviv, Israel; Liat Kishon-Rabin, Department of Communication Disorders, School of Health Pro-fessions, Tel Aviv University, Tel Aviv, Israel.

We express our appreciation to Daniel Bar-Tal and Dalit Alphandaryfor their help in the data collection and to Mirjam Hadar for valuablecomments on an earlier version of this article.

Correspondence concerning this article should be addressed to \bramBar-Tal, Department of Nursing, School of Health Professions, Tel AvivUniversity, Tel Aviv, Israel 69978. Electronic mail may be sent via theInternet to yoramb@post.tau.ac.il.

hoff (1980), for example, noted that certainty is achieved byselective focus on evidence that supports the chosen answer,regardless of contradicting evidence. Cognitive structuring mayadd previously stored information necessary to attain certaintyconcerning the validity of the inference (Anderson, 1991). Toconfirm this theory, Taylor and Crocker (1981) found that "peo-ple seem to be able to predict the future faster and more confi-dently if they have a schema for the stimulus domain than ifthey do not'' (p. 111). Finally, Fiske (1993) suggested not onlythat assimilation of information to preexisting categories is usedwhenever the cognitive task at hand is too difficult, but that itis the cognitively easier default option when there is no reasonto discredit the categorization (see also Chaiken, 1980; D'Agos-tino, 1991; Moskowitz, 1993; Neuberg & Newsom, 1993; New-man, 1991). Consequently, Fiske claimed that people can usecognitive structuring processes whenever motivated to do so.

In contrast to these widely accepted beliefs about the practi-cality and availability of cognitive structuring, we maintain thatnot only is cognitive structuring not always the easier defaultoption, but it is sometimes inaccessible, even to individualsunder high need for cognitive structure. That is, the satisfactionof the need for cognitive structure, like the satisfaction of theneed for piecemeal processing, requires certain abilities orresources.

The Need for Cognitive Structure

The need for cognitive structure (NCS) is defined as theextent of preference for using cognitive structuring, as opposedto piecemeal processes, as a means to achieve certainty. NCShas long been at the center of attention in psychological research(Bunder, 1962; Cialdini, Trost, & Newsom, 1995; Frenkel-Brun-swik, 1949; Kagan, 1972; Neuberg & Newsom, 1993; Rokeach,I960; Rydell & Rosen, 1966; Smock, 1955; Sorrentino & Short,1986; Webster & Kruglanski, 1994). Over the years it has goneunder different names, each with its particular theoretical elabo-ration (e.g., tolerance of ambiguity, dogmatism, open mind-edness, certainty orientation, need for cognition, desire for sim-ple structure, personal need for structure, need for cognitive

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COGNITIVE STRUCTURING 1159

closure, and preference for consistency). Frenkel-Brunswik(1949), for example, suggested that intolerance of ambiguityis a preference for familiarity, symmetry, definiteness, and regu-larity. This also implies a tendency toward premature, unquali-fied black-and-white solutions and oversimplified dichotomiz-ing. Smock (1955) argued that intolerance of ambiguity reflectsthe striving for a stable or familiar environment. Rokeach (1960)proposed that an open-minded person possesses a cognitive be-lief system oriented toward new beliefs or information, whereasthe closed-minded person is oriented toward familiar or predict-able events. Roney and Sorrentino (1987) claimed that cer-tainty-oriented people are basically black-and-white thinkerswho use highly distinct and structured categories and tend tomaintain certainty by avoiding or ignoring inconsistency or am-biguity. In contrast, uncertainty-oriented people have morerichly developed, less differentiated categories, and they attendto and deal with inconsistency directly. Finally, Kruglanski andWebster (1996) suggested that the need for cognitive closureimplies the desire for a firm answer to a question and an aversiontoward ambiguity.

These conceptions share the assumption that the cognitiveprocesses used by high-NCS individuals to reduce uncertaintyare category based (Brewer, 1988; Fiske & Pavelchak, 1986),nonsystematic, and heuristic. In contrast, low-NCS individualsprefer to reduce uncertainty by using piecemeal or individuationprocesses. This preference is manifested in vigilant behaviorthat is based on a systematic and effortful search for relevantinformation, its evaluation, and its unbiased assimilation (Dris-coll, Hamilton, & Sorrentino, 1991). It is important to note thatNCS is often—though not always explicitly—conceptualizedas a dimension that at its high pole predisposes individuals touse cognitive structuring to achieve certainty, whereas at its lowpole is associated not with indifference or low motivation toachieve certainty but with a strong tendency toward piecemealprocesses. That piecemeal-cognitive structuring represents acontinuum is best illustrated in Kruglanski's (1980, 1989) layepistemology theory and in his more recent work (Kruglanski &Webster, 1996). According to this approach, achieving certaintyrequires the discontinuation of the process of hypothesis valida-tion and alternative hypotheses generation (epistemic freezing).In terms of the present framework, even when a person uses apiecemeal process, the information has to be assimilated intohis or her knowledge process to become useful. The differencebetween piecemeal and cognitive structuring processes is onlya matter of timing of cognitive structuring processes application,of the range of categories used, and of the extent of examinationof category appropriateness. When cognitive structuring is ap-plied relatively late in the epistemic process, the cognitive struc-ture usually has to be created or calibrated on the basis ofthe available information {bottom-up process), and when theadequacy of the cognitive structure is thoroughly examinedagainst the available information, the process is characterizedas piecemeal. The use of cruder, often preexisting categories,applied very early in the process {top-down process) and with-out assessment of their adequacy for incorporating all the avail-able information, is typified as cognitive structuring process.

Although it is largely agreed that there are situational vari-ables such as information inconsistency that make it more diffi-cult to use cognitive structuring (Hastie, 1980), it was not as-sumed until recently that there might be a parallel, more stable,

traitlike characteristic. Instead, the belief was simply that indi-viduals in high need of cognitive structure are able to availthemselves of a more or less appropriate cognitive structure(Kruglanski & Webster, 1996; Moskowitz, 1993; Neuberg &Newsom, 1993; Sorrentino & Short, 1986; Webster & Kruglan-ski, 1994). Bar-Tal (1993, 1994a, 1994b), however, has arguedthat this is oversimplistic: People may differ not only in theirneed for cognitive structure but also in their ability to achieveit—an ability that is orthogonal to the need. Thus, the fact thatsome people would like to reduce their uncertainty by cognitivestructuring does not mean that they are able to do so. Similarly,the fact that other people favor reducing their uncertainty bymeans of individuating processes does not imply that they willactually do this.

The Ability to Achieve Cognitive Structure

We suggest that people may differ in their ability to achievecognitive structure (AACS) and in the extent of correspondencebetween their use of cognitive structuring, on the one hand, andtheir NCS, on the other. AACS refers to the extent to whichindividuals are able to use information processing processes(cognitive structuring or piecemeal) that are consistent withtheir level of NCS. In the case of high NCS, this means theability (a) to avoid information that either cannot be categorizedor clashes with their existing knowledge or (b) to organize theirknowledge to fit an already existing cognitive structure. In thecase of low NCS, this would involve the active and systematiccomprehension of all available information.

The idea of a variable that influences the ability to use bothcognitive structuring and piecemeal processing may seem newand odd at a first glance. However, if one accepts that the needfor piecemeal processing constitutes one end of a continuumwith the need for cognitive structuring at its other extreme,one cannot reject the possibility that the ability to satisfy thesedifferent needs may also be positioned along one dimension.Moreover, one may observe that proficiency and expertise arecharacterized by a similar combination of abilities to use bothcognitive structuring and piecemeal processing, which allowsinformation processing that is both effective and accurate. Ex-pertise, for example, is very often conceptualized in terms ofsuperior cognitive structuring. Research has clearly shown thatthe expert's knowledge base is more abstract, principled, andorganized for use than is that of the novice and that experts'superior performance can be attributed to their cognitive struc-turing (Asare & Wright, 1995; Chi, Ffeltovich, & Glaser, 1981;Fiske, Kinder, & Larter, 1983; Klein & Peio, 1989; Larkin,McDermott, Simon, & Simon, 1980; VanLehn, 1989).Schraagen (1993) demonstrated that even when experts wereconfronted with new problems, they still exhibited the schema-driven problem solving that characterized their routine problemsolving. However, the fact that experts possess and effectivelyuse a large number of schemata neither prevents them frommaking fine perceptual discriminations nor stops them fromevaluating and modifying options. Indeed, this does not hinderthem in rejecting a first reaction when they judge it inadequate(cf. Klein & Hoffman, 1993; Lesgold et al., 1988; Myles-Wor-sley, Johnston, & Simons, 1988; Ohlsson, 1996; Tabak, Bar-Tal, & Cohen-Mansfield, 1996). Thus, expertise, like AACS, ischaracterized by the ability to operate schemata successfully, as

1160 BAR-TAL, K1SHON-RABIN, AND TABAK

well as by more analytical processing in accordance with thedemands of the task at hand. Bar-Tal (1993) demonstrated thatAACS may compensate for lack of experience by showing thatjob experience and a sense of job certainty correlated signifi-cantly for low-AACS participants but not for those with highdispositional AACS. (For the relationship between certainty andcognitive structuring, see Bunder, 1962; Mayseles & Kruglanski,1987.) Presumably, for the latter participants, AACS had thesame effect on uncertainty as job experience had for the former.Thus, the possibility of the existence of a theoretical constructthat may include both cognitive structuring and piecemeal pro-cessing is supported by empirical data.

The Effect of NCS on High-AACS Individuals

Table 1 presents the four possible combinations of interactionbetween the need for and the ability to achieve cognitive struc-ture. The table shows that under high AACS, the effect of NCS issimilar to that suggested by researchers of the need for cognitivestructure (Kruglanski & Webster, 1996; Neuberg & Newsom,1993). That is, given the characterization of high-NCS peopleas users of cognitive structuring and low-NCS people as usersof piecemeal processing, the former, when compared with thelatter, are also characterized by the use of cruder categories,lower use of non-schema-consistent information, the use of top-down and heuristic processing, and greater certainty. The tablealso includes a typology based on a review of the literature,portraying the ideal types (in the sociological sense) of the twogroups. Thus, for example, repressors (Byrne, 1961), who tendto use avoidance defenses and screen out ego-threatening infor-mation, and functional impulsives (Dickman, 1990; see elabora-tion below) may serve as ideal types of the high-NCS person.Similarly, vigilants (Janis & Mann, 1977) are ideal types oflow-NCS people.

Table 1 shows that both high-AACS cells are associated with

Table 1Characteristics

AACS

of the Four

Low

Combinations

NCS

of NCS and AACS

High

Low (low piecemeal)effortless processingdysfunctional impulsivitylow self-efficacyhigh certaintyhigh use of stereotypeslow stress

High (high piecemeal)effortful processingvigilancehigh self-efficacylow certaintylow use of stereotypeshigh stress

(low cognitive structuring)effortful processinghypervigilancelow self-efficacyhigh uncertaintyobsessive compulsivenesshigh sensitizationlow use of stereotypesvery high stress

(high cognitive structuring)effortless processingfunctional impulsivityhigh self-efficacyhigh certaintyhigh repressionhigh use of stereotypeslow stress

Note. NCS - need for cognitive structure; AACS = ability to achievecognitive structure.

a sense of high self-efficacy. Because maintaining a sense ofhigh self-efficacy or self-esteem requires illusions and selectiveand biased information processing (Taylor & Brown, 1988),which in turn require high cognitive structuring (cf. Kruglan-ski & Ajzen, 1983), it is not surprising that high AACS andhigh NCS are associated with high self-efficacy. Though low-NCS individuals are obviously characterized by low cognitivestructuring and less biased processing, the present model sug-gests that they, too, may experience high self-efficacy becauseof their ability to adopt an information processing strategy thatsatisfies their need for cognitive structure.

The Effect of NCS on Low-AACS Individuals

Table 1 shows that for low-AACS people, high NCS implieslower cognitive structuring, and low NCS implies lower piece-meal processing. As regards the high-NCS cell, we suggestthat because of the lower use of cognitive structuring, theseindividuals suffer from greater uncertainty. Because this uncer-tainty cannot be resolved by cognitive structuring, it inducesmore information collection and less efficient and more effortfulinformation processing. Lower cognitive structuring does notnecessarily imply higher piecemeal processing, however. In-stead, more effortful information processing can be character-ized by hypervigilance. Janis and Mann (1977) described thehypervigilant type of decision makers as individuals who sufferfrom extreme uncertainty regarding the required decision. Con-sequently, they shift rapidly and nonsysternatically between al-ternatives, indiscriminately attentive to both relevant and irrele-vant details. According to our analysis, hypervigilant individualsare strongly motivated to reach a clear-cut decision (i.e., theyhave high NCS), but, being unable to attain cognitive structure(low AACS), they engage in a nonsystematic and disorganizedinformation search, which exposes them to even more unstruc-turable information and greater uncertainty. Thus, although theeffortful processing is common in both high-AACS-low-NCSand low-AACS-high-NCS people, the former may well be char-acterized by vigilance (piecemeal processing) and the latter byhypervigilance.

Because of the common conviction that cognitive structuringis the easy default option, the idea that high NCS may, undercertain circumstances, be connected to an effortful bottom-upinformation search rather than to the more predictable effortlesscategory based and heuristic processing seems counterintuitive.Nevertheless, the existence of interpersonal differences in AACSis supported by findings in related fields. On the basis of exten-sive data regarding the physiological, neurochemical, and behav-ioral correlates of anxiety and depression, Gray (1981, 1982,1985) has proposed the existence of a behavioral inhibitionsystem (BTS), located in the septo-hippocampal system, whosefunction is to tag certain stimuli as "important" (i.e., to selectand categorize stimuli, thus facilitating their analysis). Ac-cording to Gray, hyperreactivc BIS is associated with lowerability to ignore irrelevant information and selectively focusattention on specific, essential situational characteristics. Grayfurther suggested that individuals differ in the reactivity of theirBIS and hence in their degree of hypervigilant behavior. Individ-ual differences in the ability to develop or effectively use cate-gory nodes have been reported by others as well (Frost, Lahart,Dugas, & Sher, 1988; Shiffrin & Schneider, 1977). For example,

COGNITIVE STRUCTURING 1161

non-clinically compulsive individuals have been found to haverelative difficulty in category creation and use (Frost et al.,1988). Similarly Wiggs, Martin, Altemus, and Murphy (1996)concluded that clinical compulsives spontaneously focus theirattention on the typography of a word, whereas normal controlsattend to the entire word. Another example of an inability tofilter out schema (e.g., self-schemata) -incongruent contents thatis accompanied by motivation to maintain positive self-esteemand ego integrity is constituted by the ideal type of sensitizer(Byrne, 1961; Byrne, Barry, & Nelson, 1963). Byrne et al.(1963), for example, found a positive correlation between in-congruency measure and sensitization, in which the former rep-resents inconsistency in self-report between values (good-bad)and feelings (like-dislike) with respect to various types of be-haviors, events, or objects. Hock, Krohne, and Kaiser (1996)argued that sensitizers do not tolerate uncertainty (high NCS)yet are constantly and extensively preoccupied with enhancedinformation search. These empirical data support the possibilitythat there are individuals who tend to respond to high NCS withlow cognitive structuring (increased information search and de-creased schema-inconsistent contents).

The fourth combination in Table 1 is that of low NCS andlow AACS. This combination is less surprising than high NCSand low AACS: It is easier to conceive of people who find itdifficult to use piecemeal processes even when they are moti-vated to use them. Indeed, abundant research shows that re-source depletion diminishes people's ability to satisfy their needfor accuracy (low NCS; Fiske & Neuberg, 1990; Ford & Krug-lanski, 1995; Pendry & Macrae, 1994; Thompson, Roman,Moskowitz, Chaiken, & Bargh, 1994). Our model suggests thatlow-AACS-low-NCS people tend to use effortless rather thanpiecemeal processing. The question is whether this necessarilyimplies high cognitive structuring. In other words, can we differ-entiate between high-AACS-high-NCS and low-AACS-low-NCS people? A possible answer to this question can be foundthrough Dickman's (1990) differentiation between functionaland dysfunctional impulsivity. Functional impulsivity is the ten-dency to act with relatively little forethought when such a stylewould be optimal. It can be viewed as the tendency to usecognitive structuring when a person feels that this is the requiredprocess (high AACS, high NCS). Dysfunctional impulsivity isthe tendency to act with little forethought when a person feelsthat this tendency is a source of difficulty. Dysfunctional impul-sivity can therefore be viewed as the tendency to use effortlessprocessing when piecemeal process is required (low AACS,low NCS).1 The identification of the low-AACS-low-NCS typewith dysfunctional impulsives and the high-AACS-high-NCStype with functional impulsives may indicate an important dif-ference between the two types: Because of high-AACS-high-NCS people's higher ability to produce the desired responsecompared with low-AACS-low-NCS people, who find them-selves unable to do so, it is reasonable to assume that the formerwill experience a higher sense of control than the latter. Therewould, however, be very little to help us distinguish betweenthe information processing characteristics associated with highcognitive structuring and low piecemeal processing.2 Thus, wesuggest that both high-AACS-high-NCS and low-AACS-low-NCS types use effortless processing, which characterizes cogni-tive structuring. Therefore, the present model suggests thatwhereas for high-AACS people an increase of NCS is associated

with higher cognitive structuring and more effortless processing,an increase of NCS in low-AACS people will be associatedwith lower cognitive structuring and more effortful processing.This leads us to conclude that AACS has a moderating effecton the relationship between NCS and cognitive structuring.

Several studies have illustrated the effect of personal differ-ences in AACS. Bar-Tal (1994a) demonstrated that AACS mod-erates the effect of monitoring (cf. Miller, 1990) on psychologi-cal distress. That is, low-AACS information-seeking people tendto suffer from the greatest psychological distress, whereas high-AACS information seekers suffer least. This finding contrastswith Miller's conviction that monitoring, which drives peopleto collect information about threats they are facing, has a maineffect on anxiety and psychological distress. Bar-Tal (1994a)explained that when individuals collect information without be-ing able to structure it, they tend to suffer greater psychologicaldistress, as large unstructurable amounts of information maycause uncertainty and reduce sense of control. When a greatamount of information, however, is adequately structured, thismay lead to greater certainty and control and lower distress.More direct evidence for the moderating effect of AACS on therelationship between NCS and certainty was brought by Bar-Tal (1993). According to the traditional view of NCS, thereshould be a main effect of higher NCS leading to higher cer-tainty. (For a review of empirical findings on the relationshipbetween NCS and subjective confidence see Kruglanski & Web-ster, 1996.) Bar-Tal (1993), however, showed that a positiverelationship between NCS and certainty exists only for high-AACS individuals. Low-AACS participants' level of NCS wasnegatively related to level of certainty. Likewise, in contrast tothe prediction that high NCS should cause people to experienceless difficulty in making decisions by using premature closureand ignoring inconsistencies, Bar-Tal (1994b) demonstrated thatparticipants' AACS moderated the effect of their NCS on theirdifficulty in decision making: For high-AACS participants, anincrease in NCS resulted in significantly less difficulty in deci-sion making. Moreover, these participants also showed a sig-nificant negative correlation between difficulty experienced andtime spent dwelling on the decision. That is, the higher theirNCS, the more negative was the correlation between the diffi-culty experienced and the time devoted to make these decisions.In contrast, for low-AACS participants, higher NCS was associ-ated with greater difficulty in decision making, and a morepositive correlation was found between participants' perceptionof decision difficulty and the time they spent on it. Similarly,Bar-Tal and Haboucha (1994) demonstrated in five studies thatparticipants in the high-cognitive-structuring and low-piecemealcells (high-AACS-high-NCS and low-AACS-low-NCS) werebetter copers and were less affected by stress than those charac-terized as low in cognitive structuring or high piecemeal proces-

1 For the relationship between impulsivity and cognitive structuring,see Dickman {1985) and Dickman and Meyer (1988).

2 Brunas-Wagstaff, Bergquist, Morgan, and Wagstaff's (1996) find-ings regarding differences in information processing between functionaland dysfunctional impulsives may be viewed as a preliminary indicationof the difference between individuals with high AACS and high NCSand those with low AACS and low NCS. However, there is no empiricalevidence of differences between functional and dysfunctional impulsivesin heuristic processing and use of crude categories.

1162 BAR-TAL, KISHON-RAB1N, AND TABAK

sors (low-AACS-high-NCS or high-AACS-low-NCS). Theauthors argued that the former participants, because of highercognitive structuring, were less uncertain. Because uncertaintyhas been implicated in producing stress as well as in preventingeffective coping (Folkman, 1984; Folkman, Schaefer, & Lazarus,1979; Suls & Mullen, 1981; Warburton, 1979), it is not surpris-ing that participants who tended to use cognitive structuringcoped better and suffered less from the consequences of stress.In other words, in'the case of low-AACS participants, the highertheir NCS, the more they experienced stress, presumably be-cause of greater uncertainty resulting from their lesser abilityto satisfy their NCS. In contrast, for high-AACS participants,the higher their NCS, the faster they reduced uncertainty bymeans of cognitive structuring and, therefore, the less they alsosuffered from stress and distress.3 Finally, Bar-Tal, Spilzer, andTabak (1994) found a positive correlation, for high-AACS parti-cipants, between NCS and (a) stereotypical thinking and (b)the use of heuristic. The opposite was found for low-AACSparticipants. That is, high NCS motivates individuals to resolveuncertainty by means of cognitive structuring; however, onlysufficient AACS enables them to use schematic thinking andresolve uncertainty most effectively. (For the functionality ofstereotyping in reducing uncertainty, see Fiske, 1993.)

In all the studies reported above, the dependent variable eitherwas uncertainty or was assumed to be affected by uncertainty(e.g., stress, coping, stereotypical thinking, and decision mak-ing). Moreover, since the contents of the dependent variablesused could be attributed to the contents of the NCS and AACSscales, one could claim that the results do not confirm the sug-gested model but rather represent some artifact of the relation-ship between the contents of the scales and the dependent vari-ables. The present article consists of five studies that were de-signed to examine the validity of this model. Two of the studiesdemonstrate the moderating effect of AACS on the relationshipbetween NCS and cognitive structuring by using the selectionprocess, which is an essential part of cognitive structuring. Study1 examined the recall of schema-consistent, -inconsistent, and-irrelevant information. We predicted that because cognitivestructuring involves a selection process whereby the irrelevantand inconsistent information is omitted, participants who areeither high or low in both AACS and NCS would tend to recallmore schema-consistent information than would vigilant andhypervigilant participants. Study 2 examined the effect of AACSand NCS on the types of mistakes (omission vs. commission)participants make in an audio vigilance task. Because cognitivestructuring involves narrowing the span of attention and thescreening of stimuli (Bacon, 1974; Derryberry, 1993; Hockey,1979), and because omission (i.e., missing mistakes) meansoverselectiveness whereas commission (i.e., false alarm) impliesthe underapplication of selection rules, Study 2 suggested thathigh cognitive structuring conversely affects the respective num-bers of omission and commission mistakes. Therefore, theAACS-NCS interaction differentially affects the number ofomissions and commissions. The other three studies examinedthe moderating effect of AACS on the relationship between NCSand cognitive structuring by using generalization and simplifi-cation as indexes of cognitive structuring. Study 3 aimed todemonstrate the moderating effect of AACS on the relationshipbetween NCS and generalized attributions. Study 4 sought toillustrate the moderating effect of AACS on the relationship

between NCS as measured by personal need for structure (PNS)and the variance of personality judgments. We assumed thatbecause cognitive structuring promotes unidimensional and con-sistent judgments, a stronger negative relationship would befound between the level of PNS and the amount of varianceonly for high-AACS participants. For low-AACS participantsthis relationship would be reversed, with higher PNS being asso-ciated with a higher variance. Finally, Study 5 used a differentoperationalization of AACS as well as another measure of NCSto examine the model across a variety of dependent and indepen-dent variables.

Study 1

Recall and recognition have long served as dependent vari-ables in the study of the structure and process of informationorganization (for reviews, see Alba & Hasher, 1983; Brewer,1988; Fiske, 1993; Hastie et al., 1980). Thus, for example,Ostrom, Lingle, Pryor, and Geva (1980) showed that schema-consistent items are remembered better than schema-irrelevantitems. However, Hastie (1980) pointed out that when individualsare encouraged to integrate information about a person into aunitary impression, events that are incongruent with an initialimpression will be perceived as highly informative about thatperson's character and will receive extensive consideration dur-ing encoding. Hence, information that is incongruent with theinitial impression (schema) will be recalled better than congru-ent information. This observation seems to strongly contradictthe cognitive structuring view: "The oft-replicated advantageof incongruence seemed to fly in the face of the emphasis inschema and stereotype theories on confirmatory biases, leavingan unresolved paradox in the literatures" (Fiske, 1993, p. 160).However, Driscoll et al. (1991) demonstrated that the phenome-non of better recall of schema-incongruent information variedas a function of participants' uncertainty orientation. Althoughon the whole participants recalled a higher proportion of expec-tancy-in congruent than expectancy-congruent information, therecall advantage occurred for uncertainty-oriented but not forcertainty-oriented participants. Given that certainty-orientedpeople, being consistency seekers and black-and-white thinkers(high NCS). tend to maintain the existing cognitive structureto avoid uncertainty, it is not surprising that they were found tobe less attuned to schema-incongruent information. Further-more, Dijksterhuis, van Knippenberg, Kruglanski, and Schaper(1996) found that participants with a high (vs. low) need forclosure tended to recall less stereotype-inconsistent informationand that participants low in need for closure tended to recallmore such information than stereotype-consistent information.Other researchers (Dijksterhuis & van Knippenberg, 1995; Ma-crae, Hewstone, & Griffiths, 1993; Stangor & Duan, 1991) havefound that under high cognitive load, participants recalled morestereotype (schema) -consistent information than stereotype-inconsistent information, whereas this pattern was reversed un-der conditions of low cognitive load. Finally, Stangor and Ruble

3 In addition to the AACS X NCS interaction effect on participants'stress and psychological distress, Bar-Tal and Haboucha (1994) founda main effect of AACS, which they attributed to the higher controlexperienced by the high-AACS participants, who could exercise theirpreferred information processing to achieve certainty.

COGNITIVE STRUCTURING 1163

(1989) found that participants with strong expectations showeda better recall of expectation-congruent than -incongruent infor-mation. Thus, one could argue that the correctly recalledschema-consistent information, relative to the total informationcorrectly recalled (schema-irrelevant, -inconsistent, and -consis-tent), may serve as an index of the organization and selectionprocesses of cognitive structuring.

This study examined the recall of schema-consistent, -irrele-vant, and -inconsistent information. Because higher cognitivestructuring implies better organization of schema-consistent in-formation, on one hand, and higher filtering of schema-irrelevantor -inconsistent information, on the other, higher recall ofschema-consistent information relative to the total informationrecalled may serve as an indication of higher cognitive structur-ing. Because the AACS-NCS interaction is assumed to affectthe use of cognitive structuring or piecemeal processes, we hy-pothesized that participants whose NCS and AACS were botheither low or high would tend to recall more schema-consistentinformation than vigilant and hypervigilant participants (thosewhose AACS was high and NCS low or whose AACS was lowand NCS high). In other words, for low-AACS participants,we predicted that the amount of schema-consistent informationrecalled would decrease with the increase of NCS. In contrast,for high-AACS participants, the recall of schema-consistent in-formation would increase with the increase of NCS.

Method

Participants

Fifty nurses participated in the study, all employed in a large hospitalin Tel Aviv. Participants' average tenure was 11.42 years (SD - 9.11).

Stimuli

Nurses were given a written description of a 60-year-old male patientwho had been admitted in an emergency ward. They were requested toread the provided list of symptoms thoroughly and to state with whatcertainty they could confirm the diagnosis of a myocard infarct. The listincluded 15 symptoms, five of which were consistent with the diagnosis:pressure on the chest, pain radiating to left arm, shortness of breath,cold sweat, and nausea. Five symptoms were irrelevant: skin eruption,sore throat, inflamed glands, pain while passing urine, and itching nose.Another five symptoms were inconsistent, indicating a differential diag-nosis (i.e., tashif larea): accelerated pulse rate, lower extremity, lowlevel of PO2 (oxygen pressure in the blood) and strong leg pain/

AACS Scale. The measure of AACS was carried out with a 24-itemquestionnaire. The items were chosen to represent manifestations of thefour cells: (a) ease in using cognitive structuring (e.g., "Usually, I don'thave afterthoughts upon making a decision"); (b) difficulty in usingcognitive structuring (e.g., "Even when I am really bothered by a deci-sion I should make, I still find it hard to make up my mind and freemyself from the hassle"); (c) ease in using piecemeal processing (e.g.,"Usually I see to it that my work is carefully planned and well orga-nized"); and (d) difficulty in using piecemeal processing (e.g., "Evenif 1 make notes of things ] have to do, it is hard for me to act uponthem"). It is difficult to examine the construct validity of a new scale,such as the AACS Scale, which measures a new theoretical construct.There are, however, several measures that should be related to AACS.For example, a high score on the Repression-Sensitization (R-S) Scale(Byrne, 1961) represents inability to assimilate perceptual material intoperceptual systems (Byrne, Barry, & Nelson, 1963) and inability toavoid ego-threatening contents (i.e., inability to avoid self-schemata-

inconsistent information); therefore, high R-S can be viewed as a mea-sure of low AACS and high NCS. At its low end, the R-S Scale representsthe opposite, that is, high ability to repress and avoid ego-threateninginformation. Bonanno, Davis, Singer, and Schwartz (1991), further-more, concluded that repressors are associated with a general cognitivecapacity for avoidant processing (not only of ego-threatening material)whenever the motivation to disattend is present (high AACS and highNCS). Finally, DeBono and Snyder (1992) found that whereas repres-sors used heuristic and effortless information processing, sensitizers usedeffortful processing. Therefore, we would expect to find a negativecorrelation between scores on the R-S Scale and the AACS Scale. Indeed,such a correlation was found previously (r = — .56, p < 01) in a sampleof nurses. Also, because AACS represents efficacy in using the desiredmode of information processing, and because self-efficacy should bestrongly related to self-esteem, a positive relationship was expectedbetween AACS and self-esteem. Using Rosenberg's (1965) Self-EsteemScale, such a relationship was found earlier (r = .52, p < .01) in asample of students. In addition, the AACS Scale correlated significantly(r = .24, p< .05) with Cacioppo and Petty'sf 1982) Need for CognitionScale, In general, people with a high need for cognition prefer piecemealprocessing and accordingly expend more effort in processing information(Ahlering & Parker, 1989; Thompson, Chaiken, & Hazlewood, 1993).Finally, the AACS Scale correlated negatively (r = - . 4 1 , p < .01)with the Dysfunctional Impulsivity Scale (Diclanan, 1990). Becausethe Dysfunctional Impulsivity Scale measures a tendency to use cognitivestructuring when the preferred process is piecemeal, a negative correla-tion implies that the AACS Scale also measures, beyond easy access tocognitive structuring when desired, the ability to use piecemeal processwhen wanted.5'6 Moreover, the notion that the AACS Scale representsthe ability to use both piecemeal process and cognitive structuring whenwished was also validated in a sample of students, a case in whichboth the Functional and the Dysfunctional Impulsivity Scales (Dickman,1990) were found to contribute significantly to the explanation of AACS(R = .57). Taken together, these results show that the AACS Scalemeasures the ability to use both cognitive structuring and piecemealprocessing as wanted.

Both the AACS Scale and the NCS Scale (described below) havebeen previously validated (Bar-Tal, 1993, 1994a; Bar-Tal & Haboucha,1994). The test-retest correlation (with an interval of 5 weeks betweenmeasurements) was .86. Responses to the 24 items were on a 6-pointscale ranging from completely disagree ( I ) to completely agree ( 6 ) .

The composite AACS Scale score was the mean of responses to the 24items (Cronbach's a = .67).

NCS Scale. NCS was measured by a 20-item questionnaire, withresponses on a 6-point scale ranging from completely disagree (1) tocompletely agree (6). Because there are several questionnaires that mea-sure constructs similar to NCS (e.g., Bunder, 1962; Kruglanski, Web-ster, & Klem, 1993; Rokeach, 1960; Rydell & Rosen, 1966; Macdonald,1970; Yudkovsky, 1986), items were chosen from those questionnaires,provided they reflected only motivation and preference and not actualbehavior, as behavior represents ability as well as need. Also, itemswere chosen to reflect specific personal preferences (e.g., "I am veryannoyed when something unexpected disrupts my daily routine"; "I

4 Information that leads to a differential diagnosis is inconsistent withthe original diagnosis in the sense that it shows that the latter may beincorrect.

3 Support for the notion that cognitive structuring is not the preferredmethod of high-dysfunctional impulsives is its negative correlation withNCS Scale (r = - .27, p < .01).

fi It is interesting to note that die negative correlation between dysfunc-tional impulsivity and AACS exists even after controlling for level ofself esteem (r — —.35, p < .01). That is, the negative correlationbetween AACS and dysfunctional impulsivity cannot be explained bythe positive correlation between AACS and self-esteem.

1164 BAR-TAL, KISHON-RABIN, AND TABAK

prefer things to be predictable and certain''), as well as general attitudesand values reflecting preference for the unequivocal and absolute (e.g.,"I don't like modern paintings in which I don't know what the paintermeant"; "In order to get a good dish it is absolutely essential to followthe recipe exactly"). The composite score was the mean of responsesto the 20 items (Cronbach's a. = .82). The test-retest correlation (withan interval of 5 weeks between measurements) was .85. In terms ofconstruct validity, the NCS Scale correlated positively with Rokeach's(1960) Dogmatism Scale (r = .43), with Neuberg and Newsom's(1993) Personal Need for Structure Scale (r = .45), and with Kruglan-ski, Webster, and Klem's (1993) Need for Closure Scale (r = .68), allof which represent constructs similar to NCS. Finally, given that theNCS Scale represents a dimension both of whose ends are related tohigh need for certainty (though achieved differently in each case) andthat need for certainty, in turn, should be correlated with need for control,a curvilinear relationship between desire for control and NCS could bepredicted. Indeed, a significant curvilinear (r = .25, p < .05), but notlinear (r = .06, ns), relationship was found between Burger and Coo-per's (1979) Desire for Control Scale and the NCS Scale.

80

Low A ACS

Low NCS

High AACS

High NCS

Figure I. Mean percentage recall of schema-consistent information asa function of ability to achieve cognitive structure (AACS) and needfor cognitive structure (NCS).

Procedure

Participants were approached by the experimenter, who presented her-self as a master's nursing student and asked them to participate in adecision-making study. After completing the judgment task (certainty indiagnosing myocard rafarct, as above), participants were requested tocomplete the NCS and AACS Scales; this activity served also as fillertime (about 10 min). Then participants were requested to recall as manysymptoms as possible from the earlier described list of symptoms. Oncompletion of the recall task, participants were debriefed.

Results and Discussion

Given the orthogonal relationship between the NCS andAACS Scales (r = - .05 , ns), we divided participants into fourgroups according to the median scores of the AACS and NCSScales (3.79 and 3.80, respectively). Table 2 presents the cell

Table 2Recall of Schema-Consistent, -Inconsistent, and -IrrelevantInformation as a Function of AACS and NCS

NCS type

Low (n = 11)MSD

High(n = 15)MSD

Low (n = 14)MSD

High (n = 14)MSD

Consistent

Low

3.451.04

3.001.31

High

3.501.06

3.501.09

Schema

Inconsistent

AACS

1.551.29

1.731.03

AACS

2.571.02

1.601.65

Irrelevant

1.091.30

2.131.36

2.001.41

1.001.15

Total

6.092.55

6.872.47

8.072.50

6.102.23

Note. AACS = ability to achieve cognitive structure; NCS = need forcognitive structure.

means of the three types of information (schema-consistent,-inconsistent, and -irrelevant) that was correctly recalled. Toexamine the hypothesis, we performed a 2 x 2 analysis ofvariance (ANOVA). The dependent measure was the percentageof schema-consistent information recalled.

The analysis yielded only a significant interaction, F ( l , 46)= 8.64,/? < .01. Figure 1 contains the cell means. To examinethe source of the interaction, we performed a posteriori Tukeyb tests on the residuals (Rosnow & Rosenthal, 1989). As ex-pected, for low-AACS participants, high NCS (—6.8) was asso-ciated with significantly lower cognitive structuring than waslow NCS (9.24). In contrast, for high-AACS participants, highNCS (10.02) was associated with significantly higher cognitivestructuring than was low NCS (—7.13). No other comparisonswere significant. That is, as predicted, AACS moderated theeffect of NCS on cognitive structuring, as measured by percent-age of schema-consistent information recalled.

The fact that these results were obtained while the cognitivestructure (the diagnosis) was available to the participants im-plies that high-NCS-low-AACS participants find it difficult notmerely to construct abstract categories but also to assimilateinformation in preexisting categories. (For further discussionon the difference of the two cognitive activities, see Ford &Kruglanski, 1995; Thompson et al., 1994.) It is well knownthat the construction of abstract categories requires considerablecompetence and effort. Therefore, it is not surprising that in theabsence of an adequate knowledge structure, even high-NCSindividuals are unable to engage in cognitive structuring. Thepresent results, however, show that when characterized by insuf-ficient AACS, high-NCS individuals tend to use less cognitivestructuring even when practically it is available to them.

Not only did the present design enable us to demonstrate themoderating effect of AACS on the NCS-cognitive structuringrelationship (which results in two cognitive structuring-ef-fortless-processing and two vigilant-effortful cells), but also,within the two vigilant cells, it may help to detect the differencesbetween vigilance and hypervigilance. As suggested earlier, peo-ple with high AACS and low NCS are characterized as vigilants,whereas low-AACS-high-NCS people are typically hypervigi-lant. We further suggested that hypervigilant people, because oftheir low AACS, search indiscriminately for any information to

COGNITIVE STRUCTURING 1165

resolve their high uncertainty. This low cognitive structuring isa manifestation not of a controlled and willful cognitive processaimed at achieving a valid conclusion (as is vigilance), but ofhelplessness in the creation and effective use of the schema(Sedek & Kofta, 1990). This manifestation may be revealed inan inability to discriminate between relevant (both consistentand inconsistent) and irrelevant information. If this descriptionis correct, the inconsistent information, because of its diagnosticvalue, will be recalled better by vigilant individuals, whereas theirrelevant information will be recalled better by hypervigilantindividuals. To test this hypothesis, we calculated two indexesfor each participant of the percentage of irrelevant and inconsis-tent recalled information of the total information recalled. Next,a 2 X 2 within-between ANOVA was performed (low-AACS-high-NCS participants vs. high-AACS-Iow-NCS participants;percentage of irrelevant vs. inconsistent recalled information).The results, presented in Figure 2, show that although inconsis-tent information was recalled better by the high-AACS-low-NCS participants than by those with low AACS and high NCS(Ms = 32.94 and 23.79, respectively), the latter group betterrecalled the irrelevant information (Ms = 30.59 and 22.55, re-spectively), F(l, 26) = 4.09, p = .05. The a posteriori Tukeyb tests performed on the residuals confirmed that the two com-parisons were significant. Thus, the present results confirm thedistinction between the two types of effortful processing (highpiecemeal and low cognitive structuring). This distinctionshows that although effortful processing may under certain cir-cumstances (low AACS) be the default option of cognitivestructuring, piecemeal processing is not necessarily the defaultoption of cognitive structuring.

Although the findings of this study regarding the effect oftraitlike characteristics on the type of information recalled arecompatible with those of Dijksterhuis et al. (1996) and Driscollet al. (1991) to the effect that individuals' NCS reduces theirrecall of inconsistent information, they differ on one majorpoint, that is, the present finding that the recall rate of consistentinformation is higher than that of inconsistent information inall research groups. This finding also contrasts with those ofother researchers (Bargh & Thein, 1985; Hastie, 1980; Srull,Lichtenstein, & Rothbart, 1985). This difference may stem fromthe fact that the inconsistency in the current study was between

40

30

10

High NCS, low AACS

(Hypervigilants)

Low NCS, high AACS

(Vigilants)

• Irrelevant information D Inconsistent information

Figure 2. Differences in recall of irrelevant and inconsistent informa-tion as a function of vigilance type. NCS = need for cognitive structure;AACS = ability to achieve cognitive structure.

the schema (the diagnosis) and some of the presented symp-toms, which may indicate an alternative diagnosis; in most otherstudies, the inconsistency was among the information itemsthemselves. Another possibility is that the schema created inthis study is more salient than those in other studies because itwas presented as such to the participants rather than having tobe deduced from the available information. According to thelatter explanation, the reason for the lower recall of the inconsis-tent information is the stronger schema activation in our study(cf. Stangor & Ruble, 1989).

Study 2

Whereas Study 1 demonstrated the effect of AACS and NCSon the filtering out of schema-irrelevant and -inconsistent infor-mation, Study 2 aimed to illustrate that the selection processassociated with cognitive structuring is applicable also in thecase of nonverbal cues. Several researchers (Easterbrook, 1959;Eysenck, 1982; Kahneman, 1973) have argued that increasedstress leads to a restriction of cue use. (For connection betweenstress and cognitive structuring, see Hamilton, 1982;Jamieson & Zanna, 1989; Keinan, Friedland, & Arad, 1991;Kruglanski & Webster, 1996; Smock, 1955.) Williams, Tony-mon, and Andersen (1990) demonstrated a decrement in periph-eral vision as a result of stress. Presumably, a too widely openfilter would increase the probability of non-task-related cuesbeing tagged as relevant and therefore attracting attention. A"tightened filter," in contrast, helps to reject the nonessentialinformation. As stress increases, however, the filter becomes sodense that even task-essential information is blocked out. Thus,if stress causes cognitive structuring, which in turn leads to amore stringent selection process, the interaction between AACSand NCS, which was earlier suggested to affect cognitive struc-turing, should also affect the screening process: Individuals whotend to use vigilant or hypervigilant information processing(low-AACS-high-NCS and high-AACS-low-NCS) shouldapply lenient rules of selection, which would mean the recogni-tion of a wider range of cues as relevant. Nonvigilant individuals(low-AACS-low-NCS and high-AACS-high-NCS) can be ex-pected to apply more stringent selection rules and therefore evento filter out relevant cues.

To examine this hypothesis, we used a task typical of thesignal detection paradigm. In such a task, participants are pre-sented with a noise stimulus that either includes a signal or doesnot. The participant responds "yes" if he or she hears the signaland " n o " if only the noise was heard. Responses can be classi-fied into four groups: a yes response when the signal was present(correct response, or hit), a yes response when the signal wasabsent (commission), a no response when the signal was absent(correct rejection), and a no response when the signal waspresent (omission). The listener's decision as to whether he orshe heard the signal is based on purely sensory factors thatinfluence the discriminability of the signal and on factors associ-ated with the response bias, such as motivation, instructions,and personal bias (e.g., Davison & McCarthy, 1988; Green &Swets, 1974; Swets, Tanner, & Birdsall, 1961). McCarthy andDavison (1980) suggested that response bias (b) is a logarith-mic function of the geometric average of hits and commissionsdivided by the geometric average of correct rejections and omis-sions (.5*log(hits*commissions)/(correct rejections*omis-

1166 BAR-TAL, KISH0N-RAB1N, AND TABAK

sions)). Thus, because the numerator represents the tendencyof inclusion, and the denominator represents the tendency ofexclusion and selectiveness, higher b represents more commis-sion and less omission mistakes. We suggest that cognitive struc-turing is one of those nonsensory factors that affect decisionmaking in the signal detection paradigm. If indeed cognitivestructuring involves a selection process and a narrowing spanof attention, and if for low-AACS individuals the level of NCSis inversely related to cognitive structuring, we can predict thatfor individuals with low AACS, NCS will negatively affect thenumber of omissions and positively affect the number of com-missions- Therefore, NCS will increase the size of the responsebias. For high-AACS individuals, however, the number of omis-sions will increase with the rise of NCS, whereas commissionswill decrease as will the size of the response bias.

Method

Participants

Twenty-two men and 33 women, all non-hearing impaired, aged 20-38 (M = 26.89 years), volunteered to participate in this study.

Stimuli

A total of 80 stimuli were generated. Forty stimuli each consisted of800 ms white noise; the remaining 40 stimuli each consisted of a 400ms, 1 kHz pure tone embedded symmetrically within an 800 ms whitenoise stimulus. Four different samples of white noise were used toprevent participants from developing familiarity with the characteristicsof a particular noise sample (i.e., the "frozen noise" effect). All riseand fall times were set at 20 ms. Signal-to-noise ratio was - 1 5 dB.Stimuli were generated digitally using DADISP software, a DT-3801digital signal processing board, and an IBM-compatible 20386 computer.Stimuli were recorded randomly on an audiotape.

Measures

NCS and AACS Scales. NCS and AACS were measured by the scalesdescribed in Study 1. Cronbach's alpha for the AACS Scale was .83,and that for the NCS scale, .90.

Procedure

Stimuli were presented monaurally via TDH-49 headphones; left orright ear was determined randomly. Participants were asked to indicateon a response sheet " + " for when they heard the signal or " —" fornoise only. Prior to testing, participants were presented with easy andobvious examples to ensure that they understood the task. Participantswere also asked to respond to the AACS and NCS Scales. Half of theparticipants answered the questionnaire first and then proceeded to thelistening task, the other half were exposed to the reverse sequence. Alltesting was conducted individually and in quiet conditions.

Results and Discussion

To test the hypothesis, we divided participants into fourgroups according to the median scores of the AACS and NCS

Scales (3.85 and 3.46, respectively). Table 3 presents the fourcell means of response bias. Because NCS and AACS wereorthogonal (r - - .06 , ns), to examine the hypothesis, we per-formed a 2 x 2 ANOVA (low vs. high AACS; low vs. highNCS). The analysis yielded only a significant interaction, F( 1,51) = 4.35, p = .05. The a posteriori Tukey b tests performedon the residuals show that low-AACS-low-NCS participantshad a significantly lower response bias (—.22) than the low-AACS-high-NCS participants (.23). In contrast, high-AACS-low-NCS participants scored significantly higher (.19) thanhigh-AACS-high-NCS participants ( - .24) . Thus, according tothe hypothesis, for low AACS, the level of NCS was associatedwith lower selectiveness and wider filter (lower cognitive struc-turing). In contrast, for high AACS, the increase of NCS wasassociated with tighter filtering of cues (higher cognitivestructuring).

The present study considered two types of mistakes to repre-sent two different constructs (cognitive structuring vs. vigi-lance). This approach differs from the more prevalent one, inwhich the number of omissions (representing cognitive structur-ing) is compared with the total number of hits (representingvigilance; for review, see Hancock, 1986). The latter approachmay rest on the two following assumptions: (a) when comparingomission and commission, omissions are more important be-cause they better represent response to stress and because com-missions do not fit the theoretical conceptualization regardingthe cognitive response to stress; and (b) because cognitive vigi-lance is believed to be the more accurate and leads to the appro-priate response (Janis & Mann, 1977), it should be representedby the number of correct reactions. In contrast, the assumptionin this study is that if cognitive structuring represents selective-ness, this should consist of a continuum covering the full rangefrom overselectiveness to underselectiveness. This continuum isrepresented best by the measurement of response bias. More-over, if it is correct that stress causes an increase in NCS, theresults of this study imply that for a certain population (high-NCS-low-AACS), higher stress may be correlated with lessrather than more cognitive structuring. In fact, in Ihose studiesIhat have used the number of commission mistakes as one ofthe dependent variables, it has sometimes been found that inaddition to the decrease in correct responses, under stress, thereis also a greater incidence of false detections (e.g., Poulton &Edwards, 1974). This may imply that for certain people, the

Table 3Response Bias as a Function of AACS and NCS

AACS

LowMSDn

HighMSDn

Low

-0.440.50

14

0.280.81

15

NCS

High

-0.060.53

14

-0.221.15

12

Note. AACS = ability to achieve cognitive structure; NCScognitive structure.

need for

COGNITIVE STRUCTURING 1167

increase in stress is associated with less cognitive structuringbut no improvement in performance.7 Therefore, future researchon the effects of stress on cognitive vigilance should use bothomissions and commissions as dependent variables, as well astrying to identify the variables that may influence each type ofmistake.

Study 3

Although Study 1 and Study 2 demonstrated the effect of theNCS x AACS interaction on the selection process, it is im-portant to remember that this process is not the sole indicatorof cognitive structuring. Another major aspect of cognitive struc-turing is contributed by simplified generalizations and the useof abstract category labels, as opposed to concrete and specificones. Along these lines, Keinan et al. (1991) demonstrated theuse of larger and cruder categories (Study 1 and Study 2) aswell as a higher level of information integration (Study 3) understress. Similar results were reported by Neuberg and Newsom(1993), using PNS as an independent measure (Study 3}. Web-ster, Kruglanski, and Pattison (1995), exploring the phenome-non of linguistic intergroup bias (LIB; Boudreau, Baron, &Oliver, 1992), found a greater use of abstract language as afunction of participants' need for closure (Study 1) and levelof ambient noise (Study 2).

The present research used global self-attribution as a measureof cognitive structuring. Global self-attributions imply that theexpectation of controllability or uncontrollability is generalizedwidely across situations. Accordingly, Alloy, Peterson, Abram-son, and Seligman (1984) reported that learned helplessnessdeficits (Hiroto & Seligman, 1975) generalize from the unsolv-able situation to new, dissimilar settings only among people whoexhibit a style of attributing failure to global factors (see alsoMikulincer, 1986). Mikulincer, Yinon, and Kabili (1991), inturn, found that learned helplessness generalized deficit is corre-lated with NCS. Thus, according to the same logic, and giventhe tendency of high-NCS individuals to prefer the more generaland global over the specific, global self-attribution should becorrelated with NCS. Therefore, the present study examined themoderating effect of AACS on the relationship between NCSand the stable and global dimensions of self-attribution to nega-tive events. Because global attribution of negative events hasbeen found to be correlated with both depression and anxiety(Ahrens & Haaga, 1993; Heimberg et al., 1989), the two werehere used as covariates. We did this to ensure a measure of purecognitive structuring uncontaminated by other constructs, suchas depression and anxiety. Our hypothesis was that whereas apositive relationship between NCS and stable and global attribu-tions would be found for high-AACS participants, for low-AACS participants higher NCS would be associated with attri-butions that are less stable and more specific.

Method

ParticipantsParticipants were 104 new male recruits to the Israeli Defense Army,

all 18 years old.

MeasuresNCS and AACS Scales. NCS and AACS were measured by the scales

described in Study 1. Cronbach's alpha for AACS was .77 and for NCSwas .78.

Aitributional style. The stability and globality dimensions of partici-pants' attributions were assessed by the Expanded Attributional StyleQuestionnaire (EASQ; Peterson & Villanova, 1988). The EASQ con-sists of 24 negative events, for each of which participants provide acause, whose intemality, stability, and globality they then indicate. Inother words, they are asked to specify to what extent the main cause ofthe event (a) is something in him- or herself (intemality), (b) is some-thing diat will also exist in the future (stability), and (c) affects otherareas of his or her life (globality). For the present study, only the stabilityand globality dimensions were analyzed, and four of the original itemsdealing with job or college performance were modified to reflect eventsrelevant to the participants' new military career. Thus, for example, theitem "After your first term at school, you are on academic probation"was substituted with "^bur achievements in the initial training periodare poor." Responses to the 24 items for stability and globality are ona 6-point scale ranging from not at all (I) to to a very large extent (6).The composite stability and globality scores are the mean responses tothe 24 items (Cronbach's a — .90 and .92, respectively).

Depression and anxiety. We assessed participants' level of depres-sion and anxiety by means of the two corresponding subscales from theBrief Symptom Inventory (Derogatis & Melisaratos, 1983). Each scaleconsists of six items. Responses to the 12 items are on a 6-point scaleranging from not at all (I) to to a very large extent (6). The compositedepression and anxiety scores are the mean responses to the six items(Cronbach's a = .80 and .83, respectively).

Procedure

Participants filled out the questionnaires in a group setting during thefirst day of their basic training period. They were told that there wereno correct or incorrect answers and that they were requested only toreport their real feelings. Then they were promised that their answerswould be kept anonymous.

Results and Discussion

Table 4 presents the correlations among the study variablesand shows that, as expected, both depression and anxiety werepositively correlated with the two attribution measures. In addi-tion, AACS was negatively correlated with the two dependentvariables as well as with depression and anxiety. This correlationmay be explained by the fact that AACS reflects sense of masteryof the preferred information processing method. That is, byvirtue of being able to use their preferred method of informationprocessing (cognitive structuring or piecemeal), participantstended to suffer less from the helplessness that accompaniesdepression and anxiety.

To test the study hypothesis, we performed two hierarchicalregression analyses. In the first step, the depression and anxietyscores were introduced. In the second step, the two main effectsof AACS and NCS were examined. In the third and final step,the effect of the interaction term (NCS x AACS) was assessed.Following Dunlap and Kemery's (1987) suggestion concerningthe reduction of multicollinearity, we standardized all variablesbefore we computed the respective cross-products. Both analy-ses achieved significance. Table 5 shows that in the first step,only depression achieved significance. Although in the presentanalyses attributional style was regressed on depression rather

7 This conclusion is also consistent with the finding in Study 1 that lowcognitive structuring does not necessarily imply systematic processing ofrelevant information.

1168 BAR-TAL, KISHON-RABIN, AND TABAK

Table 4Correlation Matrix for Study 3 Variables

1.2.3.4.5.6.MSD

Variable

AACSNCSDepressionAnxietyStabilityGlobality

1

_

-.20*-.48**-.42**-.42**-.28**3.710.58

2

—.11.07

-.03.07

3.910.62

3

—73**

49**2.691.10

4

—42**44**

2.701.11

5

—.66**

2.460.77

6

—2.620.98

Note. AACS = ability to achieve cognitive structure; NCS = need forcognitive structure.*p < .05. **p < .01.

than vice versa, these results may be viewed to support thehypothesis regarding the specificity of patterns of attribution todepression rather than to anxiety. In addition to the significanteffect of depression, in the analysis of globality the interactionterm achieved significance, whereas the analysis of stabilityachieved only marginal significance (p = .09).

To interpret the source of the interactions, we calculated re-gression lines separately for high and low AACS according toone standard deviation below and above the mean. Because theanalyses were based on the z scores of the independent variables,the values were - 1 and 1, respectively. The regression coeffi-cients were calculated using the equation obtained in the finalstep. Specifically, the regression coefficient of NCS was addedto that of the interaction term after the latter was multiplied byeither - 1 or 1 (cf. Cohen & Cohen, 1983). The results of theanalyses show that the regression coefficients of the dependentvariables on NCS for low-AACS participants were negative,lability = — -22 and/?g,oha|ity = —.19. For high-AACS participants,the regression coefficients were bKTabmy = —.02 and b^ah,Mly =.13. That is, the hypothesis is supported in the case of globalitybut not for stability. In the case of low-AACS participants,higher NCS was associated with less global self-attribution(lower cognitive structuring). In contrast, the increase of NCSwas positively associated with globality (higher cognitive struc-turing) for high-AACS participants. The smaller interaction ef-fect of stability than of globality, and especially the lack ofpositive relationship for high-AACS participants between NCSand stability, may indicate that globality captures cognitivestructuring better than does stability. That is, generalizationacross situations may satisfy the need for structure better thangeneralization across time (stability).

Study 4

Like Study 3, the present study examined the moderatingeffect of AACS on the relationship between NCS and cognitivestructuring behavior. Study 4 however, differed in the operation-alizations of cognitive structuring and the measurement of NCS.The dependent measure was the variance of participants' ratingof a target person. The variance represents the extent to whichthe respondent relies on simplified and general structures inevaluating a person. A higher variance implies that the respon-dent judges along more dimensions and with greater complexity.

This was demonstrated by the finding of Srinivas and Motowidlo(1987) that ratings provided by participants who completedan in-basket task under stress showed lower variance acrossperformance dimensions than ratings provided by participantswho completed the same task without stress.

In addition, the present study uses Thompson. Naccarato, andParker's (1989, 1992) Personal Need for Structure (PNS) Scaleas a measure of need for simple structure rather than the NCSScale measure used in the previously presented studies. Previousresearch has shown that people high in PNS tend to organizeboth social and nonsocial information in less complex ways,to stereotype others, to form spontaneous trait inferences, toassimilate impressions to primed construct, and to completetheir research requirements on time (Moskowitz, 1993; Neu-berg & Newsom, 1993; Thompson et al., 1994). In the presentresearch, participants were requested to judge a ninth-gradestudent on 11 traits on the basis of an essay the student wrote.In terms of the PNS conceptualization, there should have beena negative correlation between the variance of the participants'rating of a target person and their PNS. In contrast, the presentmodel suggests that the relationship between PNS and varianceof personality ratings is moderated by level of AACS. That is,a negative correlation between the two variables should havebeen found only for high AACS. For low AACS, higher PNSshould have been associated with a higher variance.

Method

Participants

Participants were 70 female teachers who were studying in an aca-demic bachelor of education program. Their average age was 30.49 years(SD = 8.21), and their average seniority as teachers, 5.61 years (SD =8.19).

Stimuli

Participants received an essay entitled "Suppose you are a scientist,what is the scientific discovery you would like to make? Please describe

Table 5Hierarchical Regression of Stability and Globality on AACS,NCS, and the Interaction Between Them, Controlling forDepression and Anxiety

Variable

Step 1DepressionAnxiety

Step 2AACSNCS

Step 3NCS X AACS

B

0.320.10

-0.19-0.10

0.10

Stability

R~

.28

.05

.03

T

3.19**0.94

2.60*1.66

1.71

B

0.280.25

-0.030.00

0.16

Globality

R2

.25

.00

.03

T

2.10*1.88

0.300.02

2.01*

Note. AACS = ability to achieve cognitive structure; NCS = need forcognitive structure.*p < .05. **p < .01.

COGNITIVE STRUCTURING 1169

its characteristics and advantages." The one-page essay, originally writ-ten by a ninth-grade high school student, was selected by two expertsfrom 133 essays and was judged to be average in quality.

Measures

AACS Scale. The AACS Scale used in this study is the same as thatdescribed in Study I, and its Cronbach's alpha in this study was .80.

PNS Scale. The scale consisted of 11 items. The response to eachof these items was on a 6-point scale ranging from completely disagree(1) to completely agree (6). The composite PNS score is the mean ofresponses to the 11 items (Cronbach's a = .81).

Target personality traits. Participants were presented with 11 bipolarOsgood's semantic differential traits: diligent-lazy, smart-dumb, hon-est-dishonest, polite-rude, intellectually alert-not intellectually alert,friendly-unfriendly, advanced-primitive, warm-cold, cunning-candid,confident-insecure, broad minded-narrow minded, and generous-selfish. Responses to the 11 items were on a 7-point scale (Cronbach'sa = .72). The 11 items were submitted to a factor analysis, whichyielded three factors: The first consisted of four traits related to thetarget person's intelligence, the second consisted of his or her socialqualities, and the third contained nonsocial self traits.

Procedure

The study was conducted as part of an evaluation and measurementcourse. Participants were requested to grade the essay on a 100-pointscale and to subsequently rate its writer on the 11 bipolar scales. Theinstructions were as follows:

It is difficult to infer a writer's characteristics from his/her essay,but we often find ourselves obliged to make an evaluation basedon partial information. Therefore, based on the content of the essayand the way it is written, try to imagine the student who wrote itas vividly as possible and describe him by circling the numberexpressing your opinion the best.

Finally, participants completed the PNS and AACS Scales. After com-pleting the task, participants were debriefed.

Results and Discussion

The dependent measure was computed as the squared differ-ence between each of the 11 items and the mean of the subscaleto which the item belonged, summed over the three scales. Table6 presents the correlation matrix for the study variables. Thematrix includes participants' grading of the essay. This variablewas included in the analysis on the assumption that the gradeparticipants gave could influence their evaluation of the target

Table 6Correlation Matrix for Study 4 Variables

Variable I

1. AACS2. PNS3. Variance4. GradeMSD

- .07-.15-.153.840.60

.11

.024.020.74

—.22*

8.706.77

72.1610.94

Note. AACS = ability to achieve cognitive structure; PNS = personalneed for structure.* p < .05.

Table 7Hierarchical Regression of Ratings Variance on AACS, PNS,and the Interaction Between Them, Controlling for Grades

Variable B R2

Step 1Grade

Step 2AACSPNS

Step 3PNS X AACS

1.64

-1.060.86

-2.78

.05

.03

.10

1.81

1.260.91

2.63**

Note. AACS = ability to achieve cognitive structure; PNS = personalneed for structure.**p < .01.

person's traits. To test the study hypothesis, we performed athree-step hierarchical regression analysis in which grade wasentered in the first step, the two main effects (PNS and AACSScale scores) were introduced in the second step, and finallythe effect of the interaction term was examined in the third step.The regression as a whole achieved significance. Table 7 showsthat only the interaction term achieved significance. The exami-nation of the source of the interaction revealed that for lowAACS, higher PNS is associated with higher variance of rating(b = 3.45). In contrast, for high-AACS participants, higherPNS is associated with lower variance (b = -2.11).8 Thus, aspredicted, AACS moderated the effect of PNS on participants'dispersion of ratings.9

Study 5

So far, the moderating effect of the ability to achieve cognitivestructuring has been examined by means of the AACS Scale.Although the validity of the conceptual model would benefitfrom the use of additional operationalization of the concepts, itis not easy to replace the AACS Scale with a different scalemeasuring a similar construct, as AACS is a new concept. How-ever, as mentioned in our introduction and in Study 1, the com-bined measurement of functional and dysfunctional imputsivityis very closely related to the concept in question. In terms of ourconceptualization, high functional impulsivity implies cognitivestructuring under high NCS (high AACS). Low functional im-pulsivity implies low cognitive structuring under high NCS (lowAACS). High dysfunctional impulsivity, on the other hand, im-plies high cognitive structuring under low NCS, which reflectslow AACS. Low dysfunctional impulsivity means that underlow NCS the individual tends to use less cognitive structuring

8 The interpretation of the interaction in Study 4 and Study 5 wasdone as described in Study 3.

9 To avoid the possibility that the results obtained were artifacts re-sulting from some of the target person's traits being related to intelli-gence, we repeated die analysis, using as dependent measure the varianceof only the seven items that were completely unrelated to the targetperson's quality of performance. The results show an even stronger effectof the PNS X AACS interaction (6 = -2.40, r = 3.18, p < .01).

1170 BAR-TAL, KISHON-RABIN, AND TABAK

and more piecemeal processing (high AACS). Thus, the combi-nation of the two traits may serve as a fair proxy of the AACS,in which the high-functional and low-dysfunctional impulsivesare high in AACS, too. In contrast, low-functional and high-dysfunctional impulsives have a low AACS.

As measures of NCS, the present study applies two scales:(a) the PNS Scale, described in Study 4, and (b) the Need forCognition (NFC) Scale (Cacioppo & Petty, 1982). The NFCScale taps motivation based on intrinsic enjoyment of effortfulcognitive activity. Thus, NFC represents low NCS. Indeed, high-NFC individuals show more curiosity and tend to be more easilypersuaded by high-quality arguments, whereas low-NFC peopleare equally likely to be persuaded by both high- and low-qualityarguments. High-NFC individuals have greater recall of persua-sive arguments and expend more cognitive effort in processinginformation; they are also less prone to the primacy effect (Ahl-ering & Parker, 1989; Cacioppo, Petty, & Morris, 1983; Olson,Camp, & Fuller, 1984).

We hypothesized that AACS, operationalized as the combina-tion of functional and dysfunctional impulsivity, would moder-ate the effect of PNS and NFC on cognitive structuring. Forparticipants high on functional impulsivity and low on dysfunc-tional impulsivity, we predicted that a positive relationship be-tween PNS and cognitive structuring and a negative relationshipbetween NFC and cognitive structuring would be found. Butfor participants low on functional impulsivity and high on dys-functional impulsivity, we predicted that there would be a nega-tive relationship between PNS and cognitive structuring and apositive relationship between NFC and cognitive structuring. Inthis study, we used as a dependent variable the variance in Israelistudents' ratings of their emotions toward Palestinians. As inStudy 4, the variance served as an index of cognitive structuring,because it represents a measure of simplistic perception andunidimensional and crude categorization.

Method

Participants

Participants were 60 university students taking the course Introductionto Psychology. Their average age was 23.76 years (SD = 5.02).

Measures

NFC Scale. The NFC Scale we used was an 18-item, self-reportinstrument (Cacioppo, Petty, & Kao, 1984). Responses are on a 9-point scale ranging from very strong disagreement ( - 4 ) to very strongagreement (4). The composite NFC score is the mean of responses tothe 18 items (Cronbach's a = .84).

PNS Scale. Cronbach's alpha for the PNS Scale in the present studywas .83.

Functional and dysfunctional impulsivity. The Functional Impulsiv-ity and Dysfunctional Impulsivity Scales (Dickman, 1990) consist of11 and 12 items, respectively. Responses to the 23 items are on a 6-point scale ranging from completely disagree ( I ) to completely agree(6). The composite scores of the functional and dysfunctional scalesare the mean of responses to their items (Cronbach's a = .84 and .75,respectively). The correlation between the two scales in the presentstudy was - .45 (p < .01). The calculation of the general impulsivityscore involved the substraction of the z score for dysfunctional impulsiv-ity from the z score for functional impulsivity. Substraction was usedbecause dysfunctional impulsivity implies low AACS. The reason for

the use of standardized scores in computing the impulsivity score is thatthe means of the two scales differ (Ms = 3.51 and 2.53, respectively).

Emotions toward Palestinians scale. Emotions toward Palestinianswere measured using 11 items; participants were requested to rate on a 5-point Likert-type scale the extent to which they felt each of the followingemotions toward Palestinians: empathy, anger, disgust, guilt, contempt,pity, fear, affection, attraction, sorrow, and repulsion. The reliability ofthe scale (after reversing the negative emotions) was .75. The 11 itemswere submitted to a factor analysis, which yielded three factors: Thefirst consisted of four positive emotions, the second consisted of fivenegative emotions, and the third contained two items (pity and sorrow).The dependent measure was computed as the squared difference betweeneach of the 11 emotions and the mean of the subscale to which the itembelonged, summed over the three scales.

Procedure

The study took place over a period of 4 weeks, during which one ofthe scales was filled out each week by the participants at the beginningof their psychology class. The order of questionnaire distribution wasimpulsivity, NFC, emotions toward Palestinians, and PNS. After com-pleting the fourth task, participants were debriefed.

Results and Discussion

Table 8 presents the correlation matrix of the study variables.As expected from the assumption that high NFC represents lowNCS and that high PNS implies high NCS, there was a signifi-cant negative correlation between the two measures. For thesame reason, the two variables were correlated with the depen-dent variable in opposite directions. To test the study hypothesis,we performed two-step hierarchical regression analyses. In thefirst step the main effects of impulsivity and the measure ofneed for structure (either NFC or PNS) were introduced. In thesecond step the interaction term was examined. Both regressionanalyses as a whole achieved significance. Table 9 presents theresults of the analyses. In contrast to the previous studies, bothmain effects of NCS achieved significance. In addition, the inter-action term was significant for the analysis involving PNS andwas marginally significant (p < .06) in the case of NFC. Exami-nation of the source of the interactions reveals that, as hypothe-sized, under high impulsivity, the regression coefficient of thevariance on PNS (b = —3.42) is more negative than underlow impulsivity (b = -1 .26) . That is, higher PNS was moreassociated with cognitive structuring under high than under lowAACS. Similarly, but in the opposite direction, the regressioncoefficient of the rating variance on NFC for low-impulsivity

Table 8Correlation Matrix for Study 5 Variables

1.o3.4.MSD

Variable

ImpulsivityPNSNFCVariance

1

- .04.25*

- .120.011.05

2

—- . 3 1 *-.20*4.070.76

3

—.24*

1.410.99

4

—7.194.75

Note. PNS = personal need for structure; NCS = need for cognitivestructure.* p < .05.

COGNITIVE STRUCTURING 1171

Table 9Hierarchical Regression Analyses of the Moderating Effect ofImpulsivity on the PNS and NFC Relationship, With Varianceof Emotion Toward Palestinians

PNS NFC

Variable B R2 B R2

Step 1Impulsivity -0.48 0.67 -1.11 1.54NCS -2.01 2.42* 1.51 1.99*

.14 .10Step 2

NCS X Impulsivity -2.34 2.44* 1.01 1.95.12 .08

Note. PNS = personal need for structure; NCS = need for cognitivestructure.* p < .05.

participants (b — 0.79) is smaller than for high-impulsivityparticipants (b = 2.81). That is, NFC was more associated withlower cognitive structuring under high than under low AACS.10

Thus, the present study, like the previous ones, demonstratedthe moderating effect of AACS on the relationship between NCSand cognitive structuring. However, this study contributed twofurther findings. First, the use of impulsivity as an operationali-zation of AACS contributed to the validation of both the conceptand the measure of AACS. The similar interaction patterns ob-tained when we used impulsivity as an operationalization ofAACS and when we used the AACS Scale confirm that theresults of previous studies were not an artifact of the use of theAACS Scale. In addition, because in Study 4 we also used PNSand a cognitive structuring measure very similar to that in thepresent study, we can compare the pattern of correlations be-tween each of the operationalizations of AACS and PNS, on onehand, and between AACS and cognitive structuring measures inthe two studies, on the other (see Table 6 and Table 8) . Thefact that the two correlations are similar in both studies contri-butes to the validation of both the concept of AACS and itsaccompanying scale.

Second, the use of NFC further validates the part of the pres-ent model that suggests that under low AACS, individuals witha low NCS will tend to exhibit high cognitive structuring. Thevalidation of the model thus far has been based on measures ofNCS whose high pole represents high cognitive structuring(NCS and PNS). Although it has been proposed that the lowpole of these measures implies a high need to avoid cognitivestructuring (cf. Kruglanski & Webster, 1996), empirical evi-dence for this has been very scarce. Without this postulate,however, it is very difficult to explain why people who haveboth a low NCS and a low AACS nevertheless exhibit cognitivestructuring behavior. The use of NFC in the present study asa measure of NCS validates our interpretation because NFCrepresents high need to avoid cognitive structuring. Thus, thefact that for participants in this study with low AACS, higherNFC was associated with lower variance implies that this lowAACS causes people who are motivated to use piecemeal pro-cessing (low NCS) to revert to cognitive structuring as a meansto achieve certainty.

General Discussion

In the present article, we predicted that because level of NCSis associated with the preference to resolve uncertainty throughcognitive structuring or individuating processes, and becauseAACS level is associated with the ability to use the preferredprocess in order to achieve certainty, high-AACS participantswould show cognitive behavior that is consistent with their levelof NCS. High-AACS participants who are low in NCS wouldtherefore tend to use more piecemeal effortful processing andless cognitive structuring than those with high NCS. In contrast,we predicted that low-AACS participants with high NCS wouldbe unable to use their preferred process (cognitive structuring)to resolve uncertainty; therefore, they would use more effortfulprocesses than low-NCS participants, who resort to effortlesscognitive structuring because of their inability to use their pre-ferred (piecemeal) process.

The results of the five studies validated this hypothesis. Therobustness of the findings stems not only from the fact that theinteraction effect was significant in all five studies but alsofrom the variety of operationalizations of the dependent andindependent variables. Thus, Study I and Study 2 used depen-dent measures that demonstrated the selectiveness associatedwith cognitive structuring. In the remaining three studies, thedependent variables demonstrated the use of more crude catego-ries that represent simplified abstractions associated with cogni-tive structuring. In addition, NCS was measured by three differ-ent scales. Finally, AACS was measured by two different opera-tionalizations. Hence the effect of the interaction between theneed and ability to achieve cognitive structure, demonstrated inthis article, cannot be attributed to an unknown artifact associ-ated with the operationalization of either the independent ordependent variables.

By showing that participants with a high need for cognitivestructure but a low ability to achieve it exhibited low cognitivestructuring behaviors, the present results further confirm thenotion that cognitive structuring is not simply a default optionthat can be accessed if and when needed. This puts a questionmark behind the widely accepted idea that motivation or limitedresources are sufficient causes for effortless processing (Der-ryberry & Tucker, 1991; Fiske, 1993).

The simplistic idea that motivational control of attention char-acterizes human information processing may be viewed to reston three assumptions: (a) Cognitive structuring has a clearlyadaptive function in that it helps focusing attention on the mostimportant information; (b) cognitive structuring is the easy de-fault option of information processing; and (c) because of itsfunctionality and availability, everybody can use cognitive struc-turing whenever necessary. Ample research has shown that cog-nitive structuring indeed has a major adaptive role in that itfocuses attention on the essential elements of the informationand eases the burden by using less effortful processes (Macrae,Milne, & Bodenhausen, 1994). Previous research done withthis model (Bar-Tal, 1993, 1994a, 1994b, 1994c; Bar-Tal &Haboucha, 1994) has revealed that higher cognitive structuring

10 As in Study 3 and Study 4, the analyses were repeated with the"average of the 11 emotions entered as a covariate in the first step. Theresults of these analyses were similar to those reported in Table 9.

1172 BAR-TAL, KISHON-RABIN, AND TABAK

helps to achieve certainty more effectively and therefore is asso-ciated with lower stress and more effective coping.

However, as mentioned above, the present results cast seriousdoubt on the second and third of the above assumptions. Cogni-tive structuring is not always the easy default response, andtherefore not everybody can access it when necessary. Moreover,if cognitive structuring, like individuating processes, requirescertain abilities—as shown in the present article—the assump-tion that cognitive structuring is the result of limited cognitiveor attentional resources may be erroneous. It is not very reason-able to assume that low-AACS-high-NCS individuals, whohave been found to be the lowest users of cognitive structuring,have high cognitive resources, especially when we rememberthat this group was found to have the lowest coping effectivenessand tended to suffer the highest psychological distress (Bar-Tal,1994a; Bar-Tal & Haboucha, 1994). If this line of reasoning iscorrect, the role of cognitive structuring is not necessarily tocompensate for lower cognitive or attentional resources butrather to satisfy the high NCS. Thus, the narrowing span ofattention (higher cognitive structuring) under stress may be at-tributed, at least in part, to increased NCS (Ford & Kruglanski,1995; Kruglanski & Webster, 1996; Smock, 1955) rather thanto built-in cognitive or attentional limitations. This inference isconsistent with Hirst, Spelke, Reaves, Caharack, and Neisser's(1980) conclusion that human processing capacity has virtuallyno limits.

Although the present results and conclusions run counter toa large body of research suggesting the ease and near automatic-ity of stereotyping, heuristic thinking, and so forth, certain re-search supports the idea that cognitive structuring is not alwaysthe easy default option. Sorrentino, Bobocel, Gitta, Olson, &Hewitt (1988) found, contrary to their expectations, that cer-tainty-oriented participants (high NCS) tended to use systematicprocessing under high-personal-relevance conditions. Gilbertand Hixon (1991) found that cognitive busyness may in factdecrease the likelihood of particular stereotypes becoming acti-vated. Only when the stereotype was made salient did cognitivebusyness increase the likelihood of its being applied. Thus, al-though cognitive load is commonly supposed to increase ef-fortless cognition, this study shows the opposite. Similarly,Sedek and Kofta (1990) demonstrated that participants whounderwent informational helplessness training, in spite of theirincreased uncertainty, which should have led them to increasedcognitive structuring, showed the opposite effect of reducedselective thinking.

From the present point of view, most of these findings canbe interpreted in the following way: Bar-Tal (1993, 1994b)suggested that both the need and the ability to achieve cognitivestructure are determined not only by personal characteristicsbut also by situational factors. For example, instances of stress(e.g., time pressure, cognitive load) as well as stress in generalare known to affect need for certainty and preference to usecognitive structuring (Friedland & Keinan, 1991; Jamieson &Zanna, 1989; Kruglanski & Freund, 1983; Smock, 1955). Simi-larly, factors such as priming, helplessness training, and levelof expertise were found to affect ease or difficulty in usingcognitive structuring (Baldwin, CarreII, & Lopez, 1990;Kofla & Sedek, 1989; VanLehn, 1989). Thus, in our presentterms, low availability of the schema (low AACS) coupled withcognitive busyness (high NCS) reduces cognitive structuring

(stereotyping). In contrast, under high schema availability (highAACS), cognitive busyness increases the likelihood of stereo-typing. Similarly, informational helplessness training (reductionof AACS) accompanied by high NCS reduces cognitive structur-ing. It is interesting to note that Mikulincer, Yinon, and Kabili(1991) demonstrated that NCS negatively affected cognitiveperformance (which required cognitive structuring) when parti-cipants were exposed to informational helplessness training(low AACS). An opposite effect was found for those who didnot undergo the training (high AACS).

In contrast to the epistemic behavior of the low-AACS-high-NCS type, the behavior of the low-AACS-low-NCS type isconsistent with the view of cognitive structuring as an easydefault option. Hence, it might be asked whether the occurrenceof the former type is a mere anomaly in an otherwise correctview of cognitive structuring. The present model postulates,however, that people are not necessarily able to adopt informa-tion processing methods that satisfy their epistemic needs. Thus,in our view, and as confirmed by the present results, the inabilityto use piecemeal processing, when so desired, originates fromthe same deficiency (low AACS) that produces the inability touse cognitive structuring when so wished. Therefore, the low-AACS-high-NCS combination should be regarded not as amere abnormality but as a manifestation of a more general phe-nomenon constituted by the fact that effortful processing (hyper-vigilance) may be the default of cognitive structuring, just aseffortless processing may serve as a default of piecemealprocessing.

The one possible objection to the above assertion that bothlow AACS cells mirror each other is our rinding that cognitivestructuring is the default of piecemeal processing (in the low-NCS cell), while the default of cognitive structuring (in thehigh-NCS cell) is not piecemeal processing or vigilance, butrather hypervigilance. Our characterization of the low-AACS-low-NCS type as dysfunctional impulsive, as opposed to func-tional impulsive (high-NCS-high-AACS), however, suggeststhat although the information processing of low-AACS-low-NCS people appears to be similar to what we know about cogni-tive structuring in terms of use of cruder categories, lower use ofnon-schema-consistent information, and top-down and heuristicprocessing, it has different psychological implications (sense ofcontrol and self-efficacy). Moreover, one must remember thatthe present research did not examine all the possible attributesof cognitive structuring. For example, whereas Neuberg andNcwsom's (1993) definition of cognitive structuring includesthe creation and use of abstract mental representations, ourresearch did not examine the effect of the interaction betweenNCS and AACS on the ability to create categories. Also, it ispossible that high-NCS-high-AACS individuals differ fromlow-NCS-low-AACS individuals in their reaction to situationsthat substantially increase the need for cognitive structure. Insuch situations, their low AACS may prevent the latter individu-als from responding with a sufficient increase in their cognitivestructuring. Thus, corresponding to the distinction of effortfulprocessing into vigilance and hypervigilance, there may also bea way to separate between the two information processingmodes associated with effortless processing.

An intriguing finding of the present article is that, in contrastto previous research (Kruglanski, Webster, & Klem, 1993;Moskowitz, 1993; Moskowitz & Roman, 1992; Neuberg & New-

COGNITIVE STRUCTURING 1173

som, 1993; Thompson et al., 1994), four of the five reportedstudies showed a lack of significant correlations between themeasures of NCS and cognitive structuring. If this lack of pre-dictive power were related to the NCS Scale measure, it couldbe viewed to indicate the low validity of the scale. However,the finding in Study 4 that PNS was also unrelated to cognitivestructuring casts doubt on this possibility. The fact that theexpected relationship between NCS, as measured by PNS, andcognitive structuring was found in Study 5 may mean that thereason for the lack of significant correlation between NCS andcognitive structuring involves the nature of the dependent vari-ables used in the four initial studies. The use of relatively con-tent-free dependent variables may reduce the probability of ob-taining a significant effect of NCS (regardless of how it ismeasured) on cognitive structuring. Schaller, Boyd, \bhannes,and O'Brien (1995) reported a lack of significant correlationbetween PNS and attributional complexity (Fletcher, Danilo-vacs, Fernandez, Peterson, & Reeder, 1986)—a relatively con-tent-free measure of the level of complexity of information-organizing strategies. Another possibility is that the samplesused in most studies that have reported a main effect of NCSon cognitive structuring behavior do not equally represent allfour quadrants of the model. For example, college students maytend to be high in AACS.

In conclusion, the present research demonstrates that cogni-tive structuring, as operationalized by schemata application, se-lectiveness, and narrowing span of attention, cannot be ex-plained by mere motivation for simplified, relatively homoge-neous, well-defined, and distinct structures, whose function itis to enable a clear and certain worldview. Similarly, the prefer-ence for controlled and systematic information processing is notsufficient for the manifestation of such processing. Rather, wesuggest that the relationship between these motivations and ac-tual cognitive behavior is moderated by people's AACS. Thisimplies that research that examines motivational effects on cog-nitive structuring, as well as on its consequences (e.g., stereotyp-ing, cognitive biases, heuristic), should not overlook the moder-ating effect of AACS.

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Received February 26, 1996Revision received December 23, 1996

Accepted January 8, 1997 •